TURN DO WN THE H E AT: C L IM AT E E X T RE ME S , R EGION A L IMPA C TS, A N D TH E C A SE FOR R ESILIENCE
Box 2.1 Climate Sensitivity Climate sensitivity (more specifically equilibrium climate sensitivity [ECS]) is defined as the change in global mean surface temperature at equilibrium following a doubling of atmospheric carbon dioxide (CO2) concentrations. It is a measure of the longterm response of the climate system to a sustained increase in radiativea forcing. Research efforts are continuing to better constrain ECS. Recent studies indicate that both the high end (Fasullo and Trenberth 2012) and the low end (Amundsen and Lie 2012) cannot be excluded, while the current range of results for the most advanced climate models (Andrews et al. 2012) and reconstructions of climatic records over the last 65 million years (E. J. Rohling et al. 2012) confirm the “likely” range given in the AR4 assessment. The probabilistic global mean climate projections in this section consider the AR4 assessment as still being representative of our current understanding of the ECS and use an intermediate (that is, neither the most optimistic nor the most conservative) interpretation of it (Rogelj et al. 2012b). Note that in projections from more complex models (such as the CMIP5 models analyzed for temperature, precipitation, and aridity projections in this report), climate sensitivity is not a predefined model parameter but is emerging from all the feedback processes included in the model. In the context of climate change, the IPCC AR4 defines this as “a measure of the influence a factor has in altering the balance of incoming and outgoing energy in the Earth-atmosphere system and is an index of the importance of the factor as a potential climate change mechanism.”
a
Unlike global warming, for sea-level rise, the models consistently underestimate the accelerating rise in sea levels compared to observations (Figure 2.3). Along with observations, Figure 2.3 shows projections for sea-level rise by ice-sheet and ocean models reported in the IPCC’s Third and Fourth Assessment Reports. Remarkably, the models are not able to keep pace with observed sea-level rise, which rises 60-percent faster compared to the best estimates from models. This mismatch initiated the development of “semi-empirical” models (e.g., Rahmstorf 2007; Kemp et al. 2011) that constrain model parameters by centuries to millennia of observations.11 Based on these parameters, such models project changes that by 2100 are generally higher than the process-based models by around 30–50 percent (see World Bank 2012 for more background).
How Likely is a 4°C World? The previous Turn Down the Heat report estimated that current emission reductions pledges by countries worldwide, if fully implemented, would likely lead to warming exceeding 3°C before 2100. New assessments of business-as-usual emissions in the absence of strong climate mitigation policies (Riahi et al. 2013; Kriegler et al. 2013; Schaeffer et al. 2013), as well as recent reevaluations of the likely emission consequences of pledges and targets adopted
Figure 2.2: Global-mean surface-air temperature time series unadjusted (thin pink line) and adjusted for short-term variability (red line)
Figure 2.1: Time series from the instrumental measurement record of global-mean annual-mean surface-air temperature anomalies relative to a 1851–80 reference period
Solid black lines represent the 11-year running mean. Vertical dashed lines indicate three of the largest recent volcanic eruptions. Coloring of annual-mean temperature bars from 1950 onward indicate “neutral years” (grey), as opposed to warming El Niño (red) and cooling La Niña ENSO events (blue). Sources: Jones et al. (2012); Morice et al. (2012) for temperature record, ENSO years from NOAA (adapted from NOAA - http://www.ncdc.noaa.gov/sotc/ global/2012/13).
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The blue range represents model results from IPCC Third Assessment Report and the green range from IPCC AR4. Source: Adapted from Rahmstorf et al. (2012). 11 Data dating back more than about 150 years is generally from reconstructions of
past climatic circumstance obtained by proxy data, i.e. observational evidence from which past climate changes can be derived.